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Record W2057094016 · doi:10.1080/14786419.2014.940944

Variation in oil content, fatty acid and phytosterols profile of<i>Onopordum acanthium</i>L. during seed development

2014· article· en· W2057094016 on OpenAlexaff
Moufida A. OUESLATI, Justin B. Renaud, Hanen Ghazghazi, Sadok Boukhchina, P. Mayer

Bibliographic record

VenueNatural Product Research · 2014
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStigmasterolCampesterolStearic acidPalmitic acidFood scienceChemistryRipeningLinoleic acidErucic acidOleic acidFatty acidPhytosterolBotanyHorticultureBiologyCholesterolSterolBiochemistryChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

This study has determined oil, fatty acid (FA) and phytosterols content during the ripening of the Tunisian Onopordum acanthium L. seeds. In total, nine FAs and six phytosterols were identified. The main FAs were linoleic acid (0.18-8.06 mg/g of seed) followed by oleic acid (0.051-2.45 mg/g of seed), palmitic acid and stearic acid. Pentadecanoic acid was detected, for the first time, in unripe fruits and the two last stages of development were characterised by a relative abundance of erucic acid. Overall, β-sitosterol (34.5-77.79% of total sterols) was the major 4-desmethylsterols during maturation. The first episodes of growth were characterised by the best amounts of stigmasterol and campesterol, while stigmastanol and Δ7 sitosterol had quoted the semi-ripe and fully ripe fruits; however, cholesterol was absent. These findings are useful in understanding a potential new source of important natural compounds (Phytosterols and USFA) found in this fruit and when harvest should be undertaken to optimise desired FA and phytosterols content.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.325
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2014
Admission routes1
Has abstractyes

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